Evidence for long memory in focal seizure duration

Abstract

Objective A major source of disability for people with epilepsy involves uncertainty surrounding seizure timing and severity. Although patients often report that long seizure‐free intervals are followed by more severe seizures, there is little experimental evidence supporting this observation. Optimal characterization of seizure severity is debated; however, seizure duration is associated with seizure type and can be quantified in electrographic recordings as a limited proxy of clinical seizure severity. Here, using chronic intracranial electroencephalography (cEEG), we investigate the relationship between interseizure interval (ISI) and duration of the subsequent seizure. Methods We performed a retrospective analysis of 14 subjects implanted with a responsive neurostimulation device (RNS System) that provides cEEG, including timestamps of electrographic seizures. We determined seizure durations for isolated seizures and for representative seizures from clusters determined through unsupervised methods. For each subject, the median ISI preceding long‐duration seizures, defined as the top quintile of seizure durations, was compared with the median ISI preceding seizures with durations in the residual quintiles. In a group analysis, the mean seizure duration and the proportion of long‐duration seizures were compared across ISI categories representing different lengths. Results For 5 out of 14 subjects (36%), the median ISI preceding long‐duration seizures was significantly greater than the median ISI preceding shorter‐duration seizures. In the group analysis, when ISI was categorized by length, the proportion of long‐duration seizures within the high ISI category was significantly higher than that of the low ISI category (P < 0.001). Significance By leveraging cEEG and accounting for seizure clusters, we found that the likelihood of long‐duration seizures positively correlates with ISI length, in a subset of individuals. These findings corroborate anecdotal clinical observations and support the existence of capacitor‐like long memory processes governing the dynamics of focal seizures.

A Bayesian switching linear dynamical system for estimating seizure chronotypes

“…5) Other clustering algorithms or distance metrics may yield alternative clustering solutions. 6) Given evidence of long-range dependent processes in epilepsy ( 46 , 47 ), further extensions of the model to k th-order Markovian dynamics may be of interest. 7) The population analyzed in this study is likely skewed toward people with more severe epilepsy and those with genetic etiologies of epilepsy, given the high proportion of people with genetic causes of epilepsy.…”